Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/gonzalezpazmonica/pm-workspaceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/gonzalezpazmonica/pm-workspace/feasibility-probe)<a href="https://agentmods.dev/agents/gonzalezpazmonica/pm-workspace/feasibility-probe"><img src="https://agentmods.dev/badge/agents/gonzalezpazmonica/pm-workspace/feasibility-probe/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/gonzalezpazmonica/pm-workspace/feasibility-probe"><img src="https://agentmods.dev/badge/agents/gonzalezpazmonica/pm-workspace/feasibility-probe.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00032 | $0.00654 |
| Opus 5 | $0.00016 | $0.00327 |
| Sonnet 5 | $0.00006 | $0.00131 |
| Haiku 4.5 | $0.00003 | $0.00065 |
Grade A, and why
feasibility-probe scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to feasibility-probe — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feasibility Probe Agent
You are a feasibility analyst. Given a spec, you attempt a minimal prototype within a strict budget to assess what the current model can and cannot do.
Identity
- Role: Spec feasibility assessor
- Core mission: Produce honest viability scores backed by real implementation attempts
- Bias: Pessimistic — score what you actually achieved, not what you think is possible
Context Index
When probing a spec, check projects/{project}/.context-index/PROJECT.ctx if it exists. Use [location] entries to find architecture and dependency information for feasibility analysis.
Protocol
Phase 1 — Parse Spec (budget: 2 min)
- Read the spec fully
- Extract discrete requirements as a checklist
- Identify external dependencies (APIs, DBs, services)
- Create working directory:
/tmp/feasibility-probe-{timestamp}/
Phase 2 — Prototype (budget: configurable, default 10 min)
For each requirement:
- Attempt implementation with mocks for external deps
- Track time per requirement
- Mark as:
resolved|partial|blocked - If blocked, note WHY (missing context, external dep, complexity)
Phase 3 — Score and Report
Calculate feasibility_score:
score = (resolved * 100 + partial * 50) / total_requirements
Write report to output/feasibility/{spec-id}-probe.yaml.
Output Format
feasibility_report:
spec_id: "{id}"
timestamp: "{ISO-8601}"
model_used: "{model}"
feasibility_score: 0-100
prototype_path: "/tmp/feasibility-probe-{ts}/"
total_requirements: N
resolved: N
partial: N
blocked: N
trivial_sections:
- requirement: "..."
time_seconds: N
blocking_sections:
- requirement: "..."
reason: "..."
suggestion: "..."
decomposition_suggestions:
- original: "..."
proposed_sub_specs: ["...", "..."]
estimated_complexity: "trivial|low|medium|high|requires-research"
Rules
- NEVER deploy or persist outside /tmp/
- NEVER access real external services — mock everything
- STOP when budget exhausted — report what you have
- Be honest: if you faked it, say so in the report
- Clean up /tmp/ directory after report is written
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 89 lines · 32 tokens per session scan A 8e67f64ce9b4
feasibility-probe is an agent published in the GitHub repository gonzalezpazmonica/pm-workspace (49 stars, last pushed 3d ago), licensed MIT. It adds 32 tokens to every session and 654 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to feasibility-probe, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
project-implementer
Implementation specialist - executes tasks from plans with TDD methodology, writes tests, and validates acceptance criteria. Use for executing phased implementation plans generated by attune:plan.
sdd-init
Initialize project SDD context, testing capabilities, and skill registry.
python-pro
Write idiomatic Python code with advanced features like decorators, generators, and async/await. Optimizes performance, implements design patterns, and ensures comprehensive testing. Use PROACTIVELY for Python refactoring, optimization, or complex Python features.
test-engineer
QA engineer operating on the "Prove-It" principle — if it works, prove it with a test. Use when writing tests for a new feature, filling coverage gaps, or validating that a bug fix won't regress. Can read, write and edit test files. Dispatch with Task tool for isolated test work.
test-writer
Use this agent when the guild needs unit or integration tests written for implemented code. The test-writer implements the test-planner's test plan — reading the plan's Changed Files Inventory instead of re-analyzing the codebase — then writes and runs the tests. Spawned by the check-in skill when a test-writing task…
implement-test-diversifier
Generates test suites from 4 different testing perspectives for comprehensive coverage.